Generative AI for Data Science with Copilot

Microsoft via Coursera

Coursera based on 24 ratings

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Overview

"Generative AI for Data Science with Copilot" is a specialized course designed for data professionals who want to elevate their workflow by integrating generative AI tools like GitHub Copilot. As data science projects grow in complexity, leveraging AI assistance can dramatically enhance efficiency, accuracy, and innovation. This course provides a hands-on introduction to using generative AI within the data science lifecycle—including data cleaning, analysis, visualization, feature engineering, and model building. Participants will learn how GitHub Copilot and similar tools can accelerate...

Syllabus

Foundations of generative AI and Microsoft Copilot

This module provides a comprehensive introduction to generative AI, exploring its definition, key concepts like GANs, VAEs, and Transformers, and highlighting the role of Microsoft Copilot in enhancing data science workflows through code generation, data analysis, and bias mitigation. It also addresses the ethical implications of generative AI and provides practical guidance on integrating Copilot into existing data science practices.

Generative AI use cases in data science with Copilot

This module dives into practical applications of generative AI in data science, demonstrating how tools like Microsoft Copilot can be used to augment data, uncover hidden patterns, detect anomalies, and simulate scenarios for enhanced decision-making and risk management.

Data security and privacy in generative AI

This module dives into the data security and privacy challenges of generative AI, focusing on Microsoft Copilot. You'll learn about potential risks like data breaches and the creation of misleading information, while also exploring strategies and techniques to safeguard data and ensure responsible AI use.